3 PIM Best Practices for Distributors – Featuring Advice from Animal Supply

By Kerry Young on Aug 28, 2020

Modern market drivers are steering today’s distributors into new territory. Digital sales channels, disrupted supply chains, manufacturers going direct-to-consumer – it’s all added a sense of urgency around embracing innovation. Product Information Management (PIM) provides a path forward, particularly if distributors follow a few key strategies.

Winshuttle’s EnterWorks PIM customer Animal Supply recently shared what’s made a big difference for their business. (You can hear their full story in our new webinar)

The following three best practices are drawn from their experiences implementing the EnterWorks PIM platform.

#1: Use Change Management to Create a Data Management Culture

Everyone knows change is hard. Laura Schroeder, Digital Commerce Manager at Animal Supply Company, discussed the challenges of changing the culture around data and technology when she joined a few years ago.

If your company retains the same processes for too long, getting employees across departments to implement new procedures can be a chore. When you throw disparate vendors and suppliers into the mix, it makes the climb even steeper.

As Schroeder points out, that’s where change management comes to the rescue.

Employees can’t feel like a PIM implementation is happening to them. They need to feel like they’re a part of the process and can reap the benefits of the new technology in their departments.

By recruiting internal leaders to champion the project and evangelize the advantages drawn from PIM, your organization can move forward with a more unified culture.

What are a few tangible steps a company can take? First, communicate with leaders through a steering committee and regularly scheduled meetings. This empowers individuals to have their voices heard and contribute invaluable insight into the process. Second, ask specific questions about the challenges each department is facing and how attitudes about the system are evolving. This approach makes it easier to address issues individually while maintaining a broader vision of change.

#2: Don’t Neglect Data Governance and Stewardship

The computer science concept of GIGO (Garbage In, Garbage Out) applies here. The success of a data management program is only as good as the data fed into it. Establishing (and enforcing) data standards from the start is essential. It’s also important to enact processes for both the input of existing data and the flow of future data.

Recruiting stewards who oversee the governance process across your organization is a must – some companies even institute a “Data Czar“ to spearhead the operation. When all entities across the value chain have a consistent data structure – including definitions, units of measure, UPCs, price, etc. – it eliminates many frustrations that could stem from moving data out of silos and into a central repository.

Fortunately, PIM simplifies the process through features such as:

  • Golden Record Management,
  • Custom Workflows,
  • Data Match/Merge, Validation, Survivorship, and Completeness,
  • Security Control, and
  • Data Stewardship tools.

With data quality standards, data governance, and stewardship support, all internal and external partners can trust that the data they’re seeing is accurate.

#3: Don’t Try to Boil the Ocean

Attempting to achieve every lofty product data goal right at the beginning of an implementation can lead to massive headaches. It’s often wiser to take an incremental approach.

For example, due to multiple acquisitions, Animal Supply was running multiple ERPs. Instead of trying to onboard all of them to the EnterWorks PIM platform at once, Schroeder notes that the company selected a different strategy.

“We very much took an MVP (Minimum Viable Product) approach. Let’s onboard one ERP at a time. Let’s not try to boil the ocean. Let’s get one ERP up and running, then add in another one, and another one, and another one.”

Cleansing data is another example of where a modest pace of implementation makes sense. It can be a huge undertaking, but limiting the scope can make it manageable. Animal Supply cleansed their data one brand at a time, based on their top segments. By doing that, they knew they could complete 20% of their brands by their target date, accounting for 80% of their volume.

Even though it can be exciting to think about utilizing PIM to its fullest capabilities immediately, it’s typically more effective to roll changes over time. The good news? In the case of Winshuttle, the EnterWorks PIM solution can scale with you.

Distributors must adapt to a data-driven business

As Animal Supply’s experience shows, distributors don’t have to get left behind in the digital age. If they embrace technologies like PIM, they can adapt and flourish.

EnterWorks PIM customers include some of the largest distributors and wholesalers in the world. These companies leverage Winshuttle to import data faster, enrich it through enterprise collaboration, and deliver it automatically in the format required by each selling channel.

Hear Animal Supply’s PIM Story!

Listen to our new webinar to hear how this industry leader in the physical distribution of pet supply products deployed Winshuttle’s EnterWorks PIM to rise as a leader in pet supply product data. Listen Now

About the author

Kerry Young

Kerry Young joined EnterWorks in 2006 when Ennovative, Inc., the multi-channel publishing software company he co-founded, was acquired by EnterWorks. He directs EnterWorks’ operations and leads EnterWorks’ professional services and consulting organization, ensuring effective customer implementations and ongoing success. Mr. Young brings more than 25 years of technology and business management experience to EnterWorks, having served as CTO for a subsidiary of the Dow Chemical Company, and earlier as VP, Information Technology for Marshall Industries, a $1.7 billion industrial electronics distributor. He previously managed information systems for a subsidiary of McDonnell Douglas Corporation. Mr. Young holds a B.S. degree in Computer Science from Cal Poly, San Luis Obispo and an M.B.A. from California State University Fullerton.

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